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Project description

A Simulation Execution Manager for ns-3

This is a Python library to perform multiple ns-3 script executions, manage the
results and collect them in processing-friendly data structures. For complete
step-by-step usage and installation instructions, check out readthedocs.

Contributing

If you want to contribute to sem development, first of all you'll need an
installation that allows you to modify the code, immediately see the results and
run tests.

Building the module from scratch

This module is developed using
pipenv: in order to correctly
manage virtual environments and install dependencies, make sure it is installed.
Typically, the following is enough:

pip install -U pipenv

Note that, depending on the specifics of your python installation, you may need to add
~/.local/bin to your path. In case this is needed, pip should warn you
during installation.

Then, clone the repo (or your fork, by changing the url in the following
command), also getting the ns-3 installations that are used for running
examples and tests:

These two commands will run, respectively, all code contained in the docs/
folder and all tests, also measuring coverage and outputting it to the terminal.

Since we are mainly testing integration with ns-3, tests require frequent
copying and pasting of folders, ns-3 compilations and simulation running.
Furthermore, documentation tests run all the examples in the documentation to
make sure the output is as expected. Because of this, full tests are far from
instantaneous. Single test files can be targeted, to achieve faster execution
times, by substituting ./tests in the second command with the path to the test
file that needs to be run.

Building the documentation

Documentation can be built locally using the makefile's docs target:

make docs

The documentation of the current version of the package is also available on
readthedocs.

Running examples

Troubleshooting

In case there are problems with the pandas installation (this will happen in
macOS, for which no binaries are provided), use the following command for
installation (and see this pandas
issue as a reference):